- cross-posted to:
- [email protected]
- cross-posted to:
- [email protected]
OpenAI blog post: https://openai.com/research/building-an-early-warning-system-for-llm-aided-biological-threat-creation
Orange discuss: https://news.ycombinator.com/item?id=39207291
I don’t have any particular section to call out. May post thoughts tomorrow today it’s after midnight oh gosh, but wanted to post since I knew ya’ll’d be interested in this.
Terrorists could use autocorrect according to OpenAI! Discuss!
Heh
Please continue to send us your money, scaredy-ass nerds!
“you cannot conclusively disprove that we do not need more money and that we’re full of shit, so you absolutely have to give it to us so we can keep the racket going”
I keep flashing back to that idiot who said they were employed as an AI researcher that came here a few months back to debate us. they were convinced multimodal LLMs would be the turning point into AGI — that is, when your bullshit text generation model can also do visual recognition. they linked a bunch of papers to try and sound smart and I looked at a couple and went “is that really it?” cause all of the results looked exactly like the section you quoted. we now have multimodal LLMs, and needless to say, nothing really came of it. I assume the idiot in question is still convinced AGI is right around the corner though.
@self @sailor_sega_saturn it’ll be here right after those self-driving Teslas
Yall can sneer whatever you want, it doesn’t undo the room temperature superconductor made out of copper! We are going to mars with bitcoin and optimus sex bots! cope and seethe!
/s of course.
I caught a whiff of that stuff in the HN comments, along with something called “Solomonoff induction”, which I’d never heard of, and the Wiki page for which has a huge-ass “low quality article” warning: https://en.wikipedia.org/wiki/Solomonoff’s_theory_of_inductive_inference.
It does sound like that current AI hype has crested, so it’s time to hype the next one, where all these models will be unified somehow and start thinking for themselves.
Solomonoff induction is a big rationalist buzzword. It’s meant to be the platonic ideal of bayesian reasoning which if implemented would be the best deducer in the world and get everything right.
It would be cool if you could build this, but it’s literally impossible. The induction method is provably incomputable.
The hope is that if you build a shitty approximation to solomonoff induction that “approaches” it, it will perform close to the perfect solomonoff machine. Does this work? Not really.
My metaphor is that it’s like coming to a river you want to cross, and being like “Well Moses, the perfect river crosser, parted the water with his hands, so if I just splash really hard I’ll be able to get across”. You aren’t Moses. Build a bridge.
“Solomonoff induction” is the string of mouth noises that Rationalists make when they want to justify their preconceived notion as the “simplest” possibility, by burying all the tacit assumptions that actual experience would let them recognize.
it’s very worrying how crowded Wikipedia has been getting with computer pseudoscience shit, all of which has a distinct stench to it (it fucking sucks to dig into a seemingly novel CS approach and find out the article you’re reading is either marketing or the unpublishable fantasies of the deranged) but none of which seems to get pruned from the wiki, presumably because proving it’s bullshit needs specialist knowledge, and specialists are frequently outpaced by the motivated deranged folks who originate articles on topics like these
for Solomonoff induction specifically, the vast majority of the article very much feels like an attempt by rationalists to launder a pseudoscientific concept into the mainstream. the Turing machines section, the longest one in the article, reads like a D-quality technical writing paper. the citations are very sparse and not even in Wikipedia’s format, it waffles on forever about the basic definition of an algorithm and how inductive Turing machines are “better” because they can be used to implement algorithms (big whoop) followed by a bunch of extremely dense, nonsensical technobabble:
utter crank shit. I dug a bit deeper and found that the super-recursive algorithms article is from the same source (it’s the same rambling voice and improper citations), and it seems to go even further off the deep end.
Taking a look at Super-recursive algorithm, and wow…
This reads like early-1990s conference proceedings out of the Santa Fe Institute, as seen through bong water.
as someone with an interest in non-Turing models of computation, reading that article made me feel how an amateur astronomer must feel after reading a paper trying to find a scientific justification for a flat earth
This is literally the first sentence of the article, and it has a citation needed.
You can tell it’s crankery solely based on the fact that the “definition” section contains zero math. Compare it to the definition section of an actual Turing machine.
More from the “super-recursive algorithm” page:
… the Hell?
I’m not sure what that page is trying to say, but it sounds like someone got Turing machines confused with pushdown automata.
it’s hard to determine exactly what the author’s talking about most of the time, but a lot of the special properties they claim for inductive Turing machines and super-recursive algorithms appear to be just ordinary von Neumann model shit? also, they seem to be rather taken with the idea that you can modify and extend a Turing machine, but that’s not magic — it’s how I was taught the theoretical foundations for a bunch of CS concepts, like nondeterministic Turing machines and their relationship to NP-complete problems
That’s plainly false btw. The model of a Turing machine with a write-only output tape is fully equivalent to the one where you have a read-write output tape. You prove that as a student in elementary computation theory.